Although women experience clusters of symptoms during the menopausal transition, most research focuses on individual symptoms such as hot flashes. The proposed study shifts the paradigm from focusing on individual symptoms to symptom clusters (SCs). Re-analyzing data on symptoms and genetic polymorphisms, endocrine biomarkers, symptom vulnerability factors and sociobehavioral risk factors from over 500 participants in the Seattle Midlife Women's Health Study (P50 NR02323, R01 NR04141, P30 NR04001, P30 ES07033) with longitudinal follow-up spanning up to 19 years will allow us to achieve these aims: 1) identify prevalent symptom clusters during the late reproductive stage, early and late menopausal transition stages, and early postmenopause using latent class analysis;2) determine the consistency of symptom clusters as women change from one menopausal transition stage to the next;3) test models linking genetic polymorphisms, endocrine biomarkers, symptom vulnerability factors, social-behavioral risk factors and menopause-related factors to symptom clusters, and outcomes of well-being and symptom interference;4) conduct a systematic review of controlled clinical trials to identify symptoms as secondary treatment effects and adverse effects that will inform us about therapies for symptom clusters and 5) synthesize results of the empirical analyses and systematic review to develop novel symptom cluster management protocols to be tested in future feasibility studies. An interdisciplinary scientific advisory board including National Institute on Aging-funded MS-FLASH clinical trials investigators will provide our research team an opportunity for immediate sharing of our results in order to inform design of symptom cluster management approaches as well as their ongoing studies, including the generation of ancillary studies of symptom clusters and related mechanisms. PUBLIC HEALTH RELEVANCE: The results of this study will help clinicians and women, themselves, identify symptoms that cluster together and that may have different causes. Knowing which cluster of symptoms a woman has may help her clinician recommend the treatment or treatments that are most likely to work best for her. Using some of the genetic and hormone tests, as well as information about the woman's history, such as stressful experiences she has had, may help understand what causes some of her symptoms and may help her and her clinician decide on the best treatment available for her.